The miRNA-kallikrein interaction: a mosaic of epigenetic regulation in cancer
Bibliographic record
Abstract
The kallikrein-related peptidases (KLKs) constitute a family of 15 highly conserved serine proteases with trypsin- and chymotrypsin-like activities. Dysregulated expression and/or aberrant activation of KLKs has been linked to various pathophysiological processes, including cancer. Many KLKs have been identified as potential cancer biomarkers. microRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by pairing to the 3' untranslated region (UTR) of complimentary mRNA targets. miRNAs are dysregulated in many cancers, including prostate, kidney and ovarian cancers. Several studies have shown that miRNAs are involved in the post-transcriptional regulation of KLKs. However, recent evidence suggests that miRNAs can also act as downstream effectors of KLKs. In this review, we provide an update on the epigenetic regulation of KLKs by miRNAs. We also present recent experimental evidence that supports the regulatory role of KLKs on miRNA networks. The potential diagnostic and therapeutic applications of miRNA-kallikrein interactions are also discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".